Paper ID #32412Uneven Playing Field: Examining Preparation for Technical Interviews inComputing and the Role of Cultural ExperiencesStephanie J. Lunn, Florida International University Stephanie Lunn is presently a Ph.D. candidate in the School of Computing and Information Sciences at Florida International University (FIU). Her research interests span the fields of Computing and Engineer- ing Education, Human Computer Interaction, Data Science, and Machine Learning. Previously, Stephanie received her B.S. and M.S. degrees in Neuroscience from the University of Miami, in addition to B.S. and M.S. degrees in Computer Science
. Zhang, H. Xu, J. Tang, and J. Li, “Keyword extraction using support vector machine,” in international conference on web-age information management. Springer, 2006, pp. 85–96. [9] A. Schubert, W. Gl¨anzel, and T. Braun, “Scientometric datafiles. a comprehensive set of indicators on 2649 journals and 96 countries in all major science fields and subfields 1981–1985,” Scientometrics, vol. 16, no. 1-6, pp. 3–478, 1989. ´[10] F. de Moya-Aneg´on, Z. Chinchilla-Rodr´ıguez, B. Vargas-Quesada, E. Corera-Alvarez, F. Mu˜noz-Fern´andez, A. Gonz´alez-Molina, and V. Herrero-Solana, “Coverage analysis of scopus: A journal metric approach,” Scientometrics, vol
work can help other academic institutions to get some ideas how theycould establish similar program with local public-school districts.AcknowledgementThe project team wishes to acknowledge funding received by the U.S. Department of Education,Office of Career, Technical, and Adult Education, Division of Academic and Technical Education,Innovation and Modernization Program, award # V051F190072. The project also wants toacknowledge Unilever, Suffolk, VA and Jeff Larson, former adviser of the Girls in Engineeringprogram for hosting them for a field trip. 7References:[1] Virginia Department of Education. “Virginia’s 21st Century Career Pathway CYBERSECURITY”, Office of Career and Technical
that make it challenging to gain entry and to persist in the workplace [2, 3].Reports from students unable to obtain employment note that passing the technical interviews isone of the biggest issues they face in starting their career [3]. However, understanding the fullimpact of the hiring process in computing, and in particular, how it affects groups alreadyunderrepresented in computing (women, Black/African American, and Hispanic/Latinx workers),is important to creating a workplace of diverse talent [4–6]. Given the paucity of rigorousresearch surrounding the steps in the process, our motivation for this work was to create acomprehensive assessment of what hiring in computing looks like from the perspective of the jobseeker. In addition, we
. R. Quinlan, “Data mining tasks and methods: Classification: decision-tree discovery,” in Handbook of data mining and knowledge discovery. Oxford University Press, Inc., 2002, pp. 267–276.[27] S. D. Jadhav and H. Channe, “Comparative study of k-nn, naive bayes and decision tree classification techniques,” International Journal of Science and Research (IJSR), vol. 5, no. 1, pp. 1842–1845, 2016.[28] L. Breiman, “Random forests,” Machine Learning, vol. 45, no. 1, pp. 5–32, 2001.[29] A. Liaw, M. Wiener et al., “Classification and regression by randomforest,” R news, vol. 2, no. 3, pp. 18–22, 2002.[30] G. Louppe, “Understanding random forests: From theory to practice,” arXiv preprint arXiv:1407.7502, 2014.[31] S. Shalev-Shwartz and S
-solving skills by providing practice within meaningful context, and 3. increase student comfort in situations that require solving problems with computer scienceIn this experience report we detail how our teaching experiences and related research motivatedour course evolution. We consider problem solving, student experience, and technical skills withan emphasis on the relationship between practical skill acquisition and participation in computingactivities outside of students’ coursework. The course modules give students a sampling ofcomputer science topics with common problem-solving heuristics connecting them. Ourinstructional strategies involve a hybrid of teacher-directed and active learning approaches. Ourintention is that this
, no. 1 (2009): 4-10.[4] P. Li, "Virtual lab approaches for information and computer technology education," In OnlineLearning for STEM Subjects: International Examples of Technologies and Pedagogies in Use,M. Childs and R. Soetanto, Ed. Routledge, 2017, pp. 112-126.[5] K. M. Ala-Mutka, “A survey of automated assessment approaches for programmingassignments,” Computer Science Education, 15(2), pp. 83-102, 2005.[6] D. Kumar, "REFLECTIONS Tools from the education industry," ACM Inroads 9, no. 3, pp.22-24, 2018.[7] P. Li and L. Toderick, ”An Automatic Grading and Feedback System for E-Learning inInformation Technology Education,” Proceedings of 2015 ASEE Annual Conference &Exposition, Seattle, Washington. 10.18260/p.23518.[8] E. F. Gehringer
: Association for Computing Machinery, 2019, p. 196–202. [Online]. Available: https://doi.org/10.1145/3304221.3319740[15] K. Mierle, K. Laven, S. Roweis, and G. Wilson, “Mining student cvs repositories for performance indicators,” SIGSOFT Softw. Eng. Notes, vol. 30, no. 4, p. 1–5, May 2005. [Online]. Available: https://doi.org/10.1145/1082983.1083150[16] S. H. Edwards, J. Snyder, M. A. P´erez-Qui˜nones, A. Allevato, D. Kim, and B. Tretola, “Comparing effective and ineffective behaviors of student programmers,” in Proceedings of the Fifth International Workshop on Computing Education Research Workshop, ser. ICER ’09. New York, NY, USA: Association for Computing Machinery, 2009, p. 3–14. [Online]. Available: https://doi.org
, retrieved December 10, 2010 from http://www.zdnet.com/devhead/stories/articles/0,4413,2137433,00.html.3 Abedlhamid, A. Ayoub, Alhawiti, “Agent-based Interlligent Academic Advisor System”, ISSN 2319-7900, April 2015.4 Ariel G., M. Rebortera, “Issues and Concerns in the implementation of the Student’s Information System”, Knowledge E DOI 20.18502/kss.v316.2378, 2017.5 Artit, K., “Management Information System Implementation Challenges, Success Key Issues, Effects and Consequences: A case Study of Fenix System.”, Jokoping Internal Business School, May 2012.6 Hall, A. and Miro, D. (2016), A Study of Student Engagement in Project‐Based Learning Across Multiple Approaches to STEM Education Programs
research activities, have been invited to number of international conferences as Invited Speaker, chaired panel discussions and numerous international conference sessions. He has served on more than 220 international conference program committees. Furthermore, he has published number of articles in peer- reviewed international journals and conferences. He is an active member of ACM, ASEE, ASEE/PSW and CSAB.Dr. Shakil Akhtar, Clayton State University Dr. Shakil Akhtar is currently Professor of IT and Computer Science at Clayton State University. Be- fore this he was the IT Department head from July 2007 to December 2008. He was a Professor in the College of Information Technology at UAE University from 2002 to 2007
their constructive comments that helped us improve the paper.References [1] R. L. S. De Oliveira, C. M. Schweitzer, A. A. Shinoda, and L. R. Prete, “Using mininet for emulation and prototyping software-defined networks,” in 2014 IEEE Colombian Conference on Communications and Computing (COLCOM). IEEE, 2014, pp. 1–6. [2] R. R. Fontes, S. Afzal, S. H. Brito, M. A. Santos, and C. E. Rothenberg, “Mininet-wifi: Emulating software-defined wireless networks,” in 2015 11th International Conference on Network and Service Management (CNSM). IEEE, 2015, pp. 384–389. [3] R. Ruslan, M. F. M. Fuzi, N. Ghazali et al., “Scalability analysis in mininet on software defined network using onos,” in 2020 Emerging Technology in Computing
and computerorganization as they relate to computer science. Topics include computercomponents, interconnection structures, internal memory, instruction sets,number representation in computers, parallel processing, and an elementaryintroduction to assembly programming.B Textbooks / Materials: 1. Irv Englander, “The Architecture of Computer Hardware, Systems Software, and Networking - An Information Technology Approach”, Wiley, 5e, Jan 2014. 2. Computer Organization and Architecture Tutorials. https://www.geeksforgeeks.org/computer-organization-and-architecture- tutorials/ 3. Other resources will be provided as needed.C Course Objectives:The main goal of this course is to get you equipped with the
, see Table 1. Table 1. Concerns raised during the 2017’s NSF CC* PIs meeting [3]. # Concerns by PIs, Co-PIs, and attendees of 2017 NSF CC* meeting 1 “Very difficult to find, or nonexistent - difficult to retain (CI engineers)” 2 “Largest challenge was in the area of time to hire... ended up taking 10 months… (difficult to find CI engineers with the right skills)” 3 “Candidates should have hands-on knowledge of networking, at least bachelor degree, and certifications in networking and security” 4 “Combination of education and experience” 5 “At least one tour of duty as an intern or apprentice” 6 “System & network engineering, user support experience, good communication
technical program committee (TPC) member of high quality international conferences in Digital Forensics and Security. c American Society for Engineering Education, 2020 Internet of Things Forensics in Smart Homes: Design, Implementation and Analysis of Smart Home Laboratory Shinelle Hutchinson, Yung Han Yoon, Neesha Shantaram, and Umit Karabiyik {hutchi50,yoon127,nshantar,umit}@purdue.edu Department of Computer and Information Technology Purdue UniversityAbstractThe Internet of Things (IoT) has skyrocketed to the forefront of everyone’s lives, whether theyknow it or not. IoT devices
developed for mobile devices (Android and iOS tabletsand phones) and it communicates with the JLTV’s OBD via Bluetooth. The AR application willcontain a simplistic user interface that reads diagnostic data from the JLTV, shows vehiclesensors, and allows users to create virtual dashboards to display various information. It will alsocontain interactive presentation and visualization of JLTV external and internal parts and 3Danimations for diagnostic and maintenance. The AR application will consist of two modes:Standalone Mode and AR Mode. Standalone Mode does not require a real vehicle and itcontains interactive 3D visualizations and animations for diagnostic and maintenance. The ARMode requires the presence of a vehicle and projects instructions and
Chair and Co-Chair for 12 international conferences. For recognition of my research activities, I have been invited to a number of international conferences as Invited Speaker, chaired panel discussions and numerous international conference sessions. I have served on more than 200 international conference program committees. Furthermore, I have published number of articles in peer- reviewed international journals and conferences. I am also an active member of ACM, ASEE, ASEE/PSW and CSAB.Mrs. Catrina Ann ShanasMs. Ashley Pratt, National University Ashley Pratt was born in Fontana, California and from an early age she had high expectations for herself. One of her first career aspirations was to be an astronaut, she
System. Dr. Nelson’s primary technical research interest is the behavior of structural systems. For almost 25 years he has been actively involved in evaluating the behavior of free-fall lifeboats and the development of analytical tools to predict that behavior. His research has formed the basis for many of the regulations of the International Maritime Organization for free-fall lifeboat performance. Since 1988, Dr. Nelson has served as a technical advisor to the United States Delegation to the International Maritime Organization, which is a United Nations Treaty Organization. In that capacity, he is a primary author of the international recommendation for test- ing free-fall lifeboats and many of the international
Paper ID #32282Lab Performance Evaluation via a Workshop SurveyDr. Te-Shun Chou, East Carolina University Dr. Te-Shun Chou is a Professor in the Department of Technology Systems (TSYS) at East Carolina University (ECU). He received his Bachelor degree in Electronics Engineering at Feng Chia University and both Master’s degree and Doctoral degree in Electrical Engineering at Florida International Univer- sity. He serves as the program coordinator of the Master program in Network Technology for TSYS and the lead faculty of Digital Communication Systems concentration for the Consortium Universities of the Ph.D. in
], theretention of college students is a global problem. Retaining students through graduation is anongoing challenge, costing universities millions of dollars at all levels of higher education, fromcommunity colleges to the doctoral level [3]. In the United States, college retention hasworsened over several decades, such that “in 1990, the U.S. ranked first in four-year degreeattainment among 25-34-year old; [in 2014], the U.S. ranked 12th among other countries” [4].Data from the National Center for Educational Statistics [5], show many U.S. educational leadersare aware of retention problems in higher education and are making progress in preparing andhelping students to raise the retention rate.In historically black colleges and universities (HBCUs
settings in anumber of fields that touch on human computer interaction.KeywordsCross-cultural design, UI design, Localization, Diversity, InclusionIntroductionToday’s modern world has enabled tremendous growth in international commerce, research, andeducation at unprecedented levels. In turn, our increasing reliance on the internet forcommunication and commerce in the global marketplace increases our dependence on websitesdeveloped by agencies and companies around the world. For a global marketing approach tosucceed, it must consider the needs of diverse users across multiple countries and their relatedcultures. For a company’s website to be successful in meeting its users’ needs [1] - [2],companies often either globalize (creating one website for
Outcomes / Learning ObjectivesThis course development is being supported by an internal KEEN Pedagogy Mini-Grant fromOhio Northern University. KEEN is a network of engineering faculty across many educationalinstitutions dedicated to teaching undergraduate engineers how to create personal, economic, andsocietal value by having an entrepreneurial mindset [2 and 3]. The student generated content forthis course, peer feedback, improvement video, and self-reflections are designed to assiststudents in improving their entrepreneurial mindset. Below are the specific KEEN courseobjectives [4] that students will gain with the completion of the assignments. KEEN Related Course Outcomes/Learning Objectives [4]: • Take ownership of, and express interest
]. Big Data growth has accelerated thedevelopment of new smart technologies that can support the unique demands of big data. Smarttechnologies such as MapReduce/Hadoop, Spark, NoSQL, data virtualization, data lake, cloudcomputing, Artificial Intelligence (AI), Natural Language Processing (NLP) and MachineLearning (ML) have an impact on our daily lives and will continue to be an integral part of ourfuture [3]. They have transformed the way we practice medicine, communicate, processinformation and make business decisions [1]. The use of smart technologies are evident in manydomains including retail, finance, medical, engineering, government, penal, social media andcomputing [1] , [3]. Together Big Data and new smart technologies have given rise to
, andChallenges: A Big Picture," 2015 International Conference on Computational Intelligence andNetworks, Bhubaneshwar, 2015, pp. 116-123.[2] P. Li, "Centralized and decentralized lab approaches based on different virtualizationmodels," Journal of Computing Sciences in Colleges, vol. 26, no. 2, pp. 263-269, 2010.[3] M. Stockman, "Creating remotely accessible virtual networks on a single pc to teachcomputer networking and operating systems," Proceedings of the 4th conference on Informationtechnology curriculum, pp. 67-71, 2003.[4] B. Stackpole, "The evolution of a virtualized laboratory environment," Proceedings of the 9thACM SIGITE conference on Information technology education, 2008, pp. 243-248.[5] A. Gasper, S. Langevin, W. Armitage, R. Sekar, T
as computer architectures,cryptography, networking, secure coding, secure system development, penetration testing,incidence response, tool development, operating systems internals (such as Linux), and low-level 2programming [17-21] and how and the organization’s information system operates [22-24], 2)soft skills such as team-work, problem-solving, and communication [25-28], and 3) hands-ontraining on cyber ranges [29]. Cyber range is an interactive simulated representation of anorganization’s cyber infrastructure that includes their local networks, systems, tools, andapplications that provide a safe and legal environment for learning and testing Cybersecurityoperations [30].To address this
, Benjamin Gruber, Sven Helmer, and Guerriero ´ Raimato. Automating assessment of exercises as means to decrease mooc teachers’ efforts. In Oscar Mealha, Monica Divitini, and Matthias Rehm, editors, Citizen, Territory and Technologies: Smart Learning Contexts and Practices, pages 201–208, Cham, 2018. Springer International Publishing. ISBN 978-3-319-61322-2. [3] B.S. Bloom, M.D. Engelhart, E.J. Furst, W.H. Hill, and D.R. Krathwohl. Taxonomy of Educational Objectives Handbook 1: Cognitive Domain. Pearson, 1956. [4] Lorin Anderson, David R. Krathwohl, Peter W. Airasian, Kathleen A. Cruikshank, Richard E. Mayer, Paul R. Pintrich, James
Officer (CISO)) since field certification may bethe only validation of such skills. Therefore, this work-in-process seeks to investigate the use ofa framework to examine the degree to industry employment skill variance, if any, betweenindustry and academic preparation and the perceived required skills that each group expects thegraduate to have mastered.Previous research used a systematic approach, such as DACUM, to integrate the perceptions ofpractitioners in the field with that of the academicians to establish the desired curriculum. Thisprocess is especially useful when the degree is designed to meet emerging new occupations orjob titles, such as the Chief Information Security Officer [2][3]. However, little research can befound that uses the
an online collaborativeclassroom tool to conduct their online PD for a curriculum aiming to prepare students for thesecondary school Computer Science (CS) final examination held in Ireland. The online PDsession for teachers was divided into three parts: 1) an online presentation of the concepts beingtaught, 2) breakout sessions for teachers to collaborate together and solve the algorithm, andlastly, 3) a discussion of the solutions found. The teachers who attended this online PD weresurveyed afterward to provide feedback on the effectiveness of this delivery method. The studyfound that a majority of teachers responded positively to the PD and felt that the online deliverywas just as effective as the previous in-person PDs they have attended
Dakota State University and PhD from the University of Missouri-Columbia, all in electrical engineering. Dur- ing 2001-2016 he was the Dean of the College of Engineering and Computer Science at California State University, Fullerton. Prior to that he was the Head of the Electrical Engineering Department at RIT in Rochester, NY. Fullerton Chamber of Commerce recognized him in 2015 as the ”Educator of the Year.” In 2016 he received ASEE’s ”Distinguished Educator Award” from the ECE Division. Dr. Unnikrishnan was a member of the Accreditation Committee for American Society of Engineering Education (ASEE). He was a Commissioner of the Engineering Accreditation Commission of ABET during 2008-13 and chaired the
,and ongoing work related to this collaboration. 2. ImplementationThe two courses involved in this inter-class collaboration are both upper-division computerscience technical electives. The AI class consisted of two sections, the DL class of one. Eachsection had close to 40 students enrolled. For the collaboration, teams consisted of 2-6 students.Students could select their own teams, and teams could choose their own topics subject toapproval by the respective instructor. The instructors provided a common list of suggested topicsfor both classes; about half of the teams chose topics from that list. The lab portion of thecollaboration spanned the entirety of the academic term (a quarter with ten weeks of instruction).In the first week
implies both a temporal dimension, in which organizations are improving all thetime, and a spatial dimension, in which organizations are improving all of their departments,units or divisions. In order to accomplish CI, Deming proposes utilizing the Plan-Do-Check-Act(PDCA) cycle for improvement at any stage [2]. PDCA is a 4-step cycle that repeatscontinuously through which organizations create a plan, execute it, review the results, and finallymake any corrective action before starting again.While Deming’s work was mainly directed towards business, academia took notice. The terms“Continuous Improvement” and “Total Quality Management” started to show up in highereducation research papers by the late 1980’s and early 1990’s [3]. CI then found its